标题
A BIM-data mining integrated digital twin framework for advanced project management
作者
关键词
Digital twin, Building information modeling (BIM), Process mining, Time series analysis
出版物
AUTOMATION IN CONSTRUCTION
Volume 124, Issue -, Pages 103564
出版商
Elsevier BV
发表日期
2021-02-01
DOI
10.1016/j.autcon.2021.103564
参考文献
相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。- Multi-classifier information fusion in risk analysis
- (2020) Yue Pan et al. Information Fusion
- BIM log mining: Learning and predicting design commands
- (2020) Yue Pan et al. AUTOMATION IN CONSTRUCTION
- IFC-based process mining for design authoring
- (2020) Sobhan Kouhestani et al. AUTOMATION IN CONSTRUCTION
- Data-driven decision-making for equipment maintenance
- (2020) Zhiliang Ma et al. AUTOMATION IN CONSTRUCTION
- Data-driven predictive maintenance planning framework for MEP components based on BIM and IoT using machine learning algorithms
- (2020) Jack C.P. Cheng et al. AUTOMATION IN CONSTRUCTION
- Clustering of designers based on building information modeling event logs
- (2020) Yue Pan et al. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
- Developing a Digital Twin at Building and City Levels: Case Study of West Cambridge Campus
- (2020) Qiuchen Lu et al. JOURNAL OF MANAGEMENT IN ENGINEERING
- Towards a semantic Construction Digital Twin: Directions for future research
- (2020) Calin Boje et al. AUTOMATION IN CONSTRUCTION
- Digital twin-enabled anomaly detection for built asset monitoring in operation and maintenance
- (2020) Qiuchen Lu et al. AUTOMATION IN CONSTRUCTION
- Mining event logs for knowledge discovery based on adaptive efficient fuzzy Kohonen clustering network
- (2020) Yue Pan et al. KNOWLEDGE-BASED SYSTEMS
- Roles of artificial intelligence in construction engineering and management: A critical review and future trends
- (2020) Yue Pan et al. AUTOMATION IN CONSTRUCTION
- A review of building information modeling (BIM) and the internet of things (IoT) devices integration: Present status and future trends
- (2019) Shu Tang et al. AUTOMATION IN CONSTRUCTION
- Digital Twin in Industry: State-of-the-Art
- (2019) Fei Tao et al. IEEE Transactions on Industrial Informatics
- Development of a bridge maintenance system for prestressed concrete bridges using 3D digital twin model
- (2019) Chang-Su Shim et al. Structure and Infrastructure Engineering
- Digital twinning of existing reinforced concrete bridges from labelled point clusters
- (2019) Ruodan Lu et al. AUTOMATION IN CONSTRUCTION
- BIM log mining: Exploring design productivity characteristics
- (2019) Yue Pan et al. AUTOMATION IN CONSTRUCTION
- Anomaly detection for industrial control systems using process mining
- (2018) David Myers et al. COMPUTERS & SECURITY
- Towards a data science toolbox for industrial analytics applications
- (2018) Christoph M. Flath et al. COMPUTERS IN INDUSTRY
- Digital twin-driven product design framework
- (2018) Fei Tao et al. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
- A Goal-Driven Evaluation Method Based On Process Mining for Healthcare Processes
- (2018) Tugba Gurgen Erdogan et al. Applied Sciences-Basel
- Digital Twin and Big Data Towards Smart Manufacturing and Industry 4.0: 360 Degree Comparison
- (2018) Qinglin Qi et al. IEEE Access
- A framework for integrating BIM and IoT through open standards
- (2018) Bhargav Dave et al. AUTOMATION IN CONSTRUCTION
- UAV IoT Framework Views and Challenges: Towards Protecting Drones as “Things”
- (2018) Thomas Lagkas et al. SENSORS
- Process Mining to Discover Shoppers’ Pathways at a Fashion Retail Store Using a WiFi-Base Indoor Positioning System
- (2017) Illhoe Hwang et al. IEEE Transactions on Automation Science and Engineering
- A review on time series forecasting techniques for building energy consumption
- (2017) Chirag Deb et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- Digital Twin Shop-Floor: A New Shop-Floor Paradigm Towards Smart Manufacturing
- (2017) Fei Tao et al. IEEE Access
- Design Science in the Information Systems Discipline: An Introduction to the Special Issue on Design Science Research
- (2017) March et al. MIS QUARTERLY
- Cyber-physical systems for temporary structure monitoring
- (2016) Xiao Yuan et al. AUTOMATION IN CONSTRUCTION
- Opportunities for enhanced lean construction management using Internet of Things standards
- (2016) Bhargav Dave et al. AUTOMATION IN CONSTRUCTION
- Domain-driven actionable process model discovery
- (2016) Bernardo Nugroho Yahya et al. COMPUTERS & INDUSTRIAL ENGINEERING
- A Natural-Language-Based Approach to Intelligent Data Retrieval and Representation for Cloud BIM
- (2015) Jia-Rui Lin et al. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
- Process modeling and bottleneck mining in online peer-review systems
- (2015) Wichian Premchaiswadi et al. SpringerPlus
- Building Information Modeling (BIM) application framework: The process of expanding from 3D to computable nD
- (2014) Lieyun Ding et al. AUTOMATION IN CONSTRUCTION
- Quality Dimensions in Process Discovery: The Importance of Fitness, Precision, Generalization and Simplicity
- (2014) J. C. A. M. Buijs et al. INTERNATIONAL JOURNAL OF COOPERATIVE INFORMATION SYSTEMS
- An integrated approach for ship block manufacturing process performance evaluation: Case from a Korean shipbuilding company
- (2014) Jaehun Park et al. INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
- Application of Cloud Storage on BIM Life-Cycle Management
- (2014) Lieyun Ding et al. International Journal of Advanced Robotic Systems
- Vision-based material recognition for automated monitoring of construction progress and generating building information modeling from unordered site image collections
- (2013) Andrey Dimitrov et al. ADVANCED ENGINEERING INFORMATICS
- A business process mining application for internal transaction fraud mitigation
- (2011) Mieke Jans et al. EXPERT SYSTEMS WITH APPLICATIONS
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